title: Neuroelectrical decomposition of spontaneous brain activity measured with functional magnetic resonance imaging.
abstract: Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity.
authors.affiliation: Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Zhongming
authors.initials: Z
authors.lastname: Liu
authors.affiliation: Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Jacco A
authors.initials: JA
authors.lastname: de Zwart
authors.affiliation: Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Catie
authors.initials: C
authors.lastname: Chang
authors.affiliation: Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Qi
authors.initials: Q
authors.lastname: Duan
authors.affiliation: Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: van Gelderen
authors.affiliation: Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
authors.forename: Jeff H
authors.initials: JH
authors.lastname: Duyn
mesh_terms: D000328:Adult; D001921:Brain / Q000098:blood supply* / Q000502:physiology*; D001931:Brain Mapping; D004569:Electroencephalography; D005071:Evoked Potentials / Q000502:physiology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D010100:Oxygen / Q000097:blood; D010775:Photic Stimulation; D013057:Spectrum Analysis; D013223:Statistics as Topic; D014795:Visual Pathways / Q000098:blood supply / Q000502:physiology; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: band-limited power; functional networks; resting state; spectral clustering; subspace analysis